RE: [PyMOL] multi cpu rendering

[Warren D. <wa...@de...>]

You're all right. =20

The Python interpreter can't multiprocess, but Python threads are true
operating system threads.  So all you need to do is call down from =
Python
into C or some other language, free up the global interpreter lock, and
presto, you get *real* multiprocessing without every having to write a
single line of platform-specific threading code.

Virtually every API call in PyMOL goes through this cycle, which means =
that
PyMOL rendering is indeed much faster on multi-cpu systems.  Also,
multithreaded Python programs (such as GUIs) can run concurrently with =
PyMOL
in the same process on multi-cpu systems.

The best speed-up I've seen so far was on a 12-cpu Altix with 12 =
threads,
where PyMOL rendering was about 9X faster.  Of course, for the money, =
you
should just by a Linux cluster and split your multi-frame rendering job =
over
many dual-CPU nodes. =20

Cheers,
Warren

--
Warren L. DeLano, Ph.D.                    =20
Principal Scientist

. DeLano Scientific LLC =20
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> -----Original Message-----
> From: pym...@li...=20
> [mailto:pym...@li...] On Behalf Of=20
> Kristoffer Winther S=F8rensen
> Sent: Wednesday, April 20, 2005 4:49 AM
> To: Serge Cohen
> Cc: EPF (Esben Peter Friis); Neil Ranson;=20
> PyM...@li...
> Subject: Re: [PyMOL] multi cpu rendering
>=20
> Dear Serge,
>=20
> I suggest you simply make a test.
>=20
> > Indeed if you read the documentation of Python, you'll see that the=20
> > python byte-code interpreter is not able to run multiple=20
> thread at any=20
> > given time
>=20
> I don't think the PyMOL raytracer is written in Python.=20
> Furtermore, when I raytrace in PyMOL on my dual CPU Athlon MP=20
> both CPU's are utilized (top shows 93% under linux). So it=20
> does multithread.
>=20
> Regards,
>=20
> ./ Kristoffer
>=20
>=20
>=20
>=20
>=20
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